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The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method

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  • Xiaonan Fan

    (School of Management, Dalian Polytechnic University, Dalian 116034, China)

  • Sainan Ren

    (School of Management, Dalian Polytechnic University, Dalian 116034, China)

  • Yang Liu

    (School of Management, Dalian Polytechnic University, Dalian 116034, China)

Abstract

The problems of environmental pollution and resource shortages are becoming increasingly prominent with the advances in technology and the improvements in social productivity levels. How to coordinate the innovating subjects, and strengthen the interaction and cooperation among the subjects to improve the green technology innovation efficiency (GTI efficiency) is an important issue to be solved urgently. This paper constructs a multisubject collaborative analysis framework of “government–market–society” for the GTI efficiency based on the pluralistic co-governance theory. Using 30 provinces (or regions, cities) in China from 2016 to 2020 as research samples, we analyzed the driving factors of GTI efficiency using the dynamic QCA method. Furthermore, the configuration effects of the driving factors were further analyzed in the time and spatial dimensions. The results show that: (1) The single driving factor does not constitute the requisite condition for high GTI efficiency. (2) There are three types of paths to realize high GTI efficiency: “government–market driven”, “market–society driven”, and “government–market–society synergistic promotion”. Among them, the “government–market-driven” path is subdivided into “government—internal-market driven” and “government-supported–external-market driven”. (3) In the time dimension, the “market–society driven” path has prominently enhanced its driving effect on GTI efficiency, while the driving effect of the other three paths is little changed. In the spatial dimension, the coverage of the “government-supported–external-market driven” path appears to have obvious regional differences, and the explanation degree of the central region is higher, while the other three paths do not have obvious regional differences. Based on the perspective of configuration, these research results enrich the related research on the driving factors of GTI efficiency in the time and spatial dimension. It provides enlightenment for boosting the coordinated development of regional GTI efficiency and realizing sustainable economic growth.

Suggested Citation

  • Xiaonan Fan & Sainan Ren & Yang Liu, 2023. "The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9845-:d:1175455
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    2. Yunhui Wang & Rong Zhou, 2024. "Can carbon emission trading policies promote the withdrawal of government subsidies and the green development of enterprises? Empirical evidence from China’s A-share market," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-16, December.
    3. Fan Wu & Mingyang Li & Huanshui Huang, 2024. "Innovation Ecosystems and Sustainable High Innovation Performance: Evidence from the Guangdong–Hong Kong–Macao Greater Bay Area," Sustainability, MDPI, vol. 16(21), pages 1-26, October.
    4. Yanhua Li & Tingyu Zhang, 2025. "How Does the Digital Ecosystem Foster New Quality Productive Forces? A Dynamic QCA of Sustainable Development Pathways in China," Sustainability, MDPI, vol. 17(11), pages 1-24, May.
    5. Jiarui Wang & Rong Cao & Gang Wang & Xuhui Peng, 2024. "Research on the Configuration Path of Innovation Performance of Strategic Emerging Enterprises," Sustainability, MDPI, vol. 16(21), pages 1-25, October.
    6. Yunan Wang & Jing Xiao & Zhi Xu, 2025. "Digital Transformation Drives Regional Innovation Ecosystem Resilience: A Study Based on the Dynamic QCA Method," Sustainability, MDPI, vol. 17(18), pages 1-31, September.

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